Biomarkers of nanomaterials hazard from multi-layer data.
Nat Commun
; 13(1): 3798, 2022 07 01.
Article
em En
| MEDLINE
| ID: mdl-35778420
ABSTRACT
There is an urgent need to apply effective, data-driven approaches to reliably predict engineered nanomaterial (ENM) toxicity. Here we introduce a predictive computational framework based on the molecular and phenotypic effects of a large panel of ENMs across multiple in vitro and in vivo models. Our methodology allows for the grouping of ENMs based on multi-omics approaches combined with robust toxicity tests. Importantly, we identify mRNA-based toxicity markers and extensively replicate them in multiple independent datasets. We find that models based on combinations of omics-derived features and material intrinsic properties display significantly improved predictive accuracy as compared to physicochemical properties alone.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Nanoestruturas
Tipo de estudo:
Prognostic_studies
Idioma:
En
Ano de publicação:
2022
Tipo de documento:
Article